Skill comparison

Compare agent skills before installing.

Put high-signal skills side by side and inspect quality, adoption, freshness, install readiness, use-case fit, and warnings in one place.

Comparing 2 skills

Use this as a shortlist, then open the skill detail page before adopting.

Decision summary

Strongest overall

Implement

Use this as a leading candidate, then validate the README and install path in your own agent stack.

Fastest prototype

Implement

Best first install candidate based on install readiness and adoption.

Freshest repo

super-linting

Most recent maintenance signal among this shortlist.

Signal	super-linting Set up local development linting by picking the right linters for each file type a project uses, then recording them as required pre-commit checks in AGENTS.md / CLAUDE.md and a `make lint` target. Uses the super-linter project as the live source of truth for which linters are current and popular per language. Use this skill whenever the user wants to add, choose, configure, or standardize linters for local development; asks "what linter should I use for X"; wants the agent to lint files before committing; sets up AGENTS.md/CLAUDE.md linting rules; or mentions super-linter, linting setup, pre-commit linting, or keeping linters up to date. This is for LOCAL developer/agent linting, not for authoring CI workflows.	Implement Implement work from an approved spec or ticket set, run focused and full tests, invoke code review, and commit the result to the current branch.
Quality	54/100 Needs review	100/100 Excellent
Decision verdict	53/100 Needs manual review Do a manual repository review before adding this to an agent workflow.	100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack.
Adoption	20 stars Verified outcomes are shown on each skill page	176K stars Verified outcomes are shown on each skill page
Freshness	Sep 14, 2026	Jul 17, 2026
Use-case fit	Research agents Local desktop Coding agents	Coding agents